# File Extraction: Linux
On Linux command line, you can use extract the .gz zipped file using gzip.

sudo apt-get update
sudo apt-get install gzip
gunzip -k 25ja002_fig1_data.gzip

# File Extraction: Windows + MAC
On Windows + MAC, you can extract the gz file with a standard file unzipper like 7Zip.
https://www.7-zip.org/
https://apps.apple.com/id/app/unzip-rar-zip-7z-unarchiver/id1537056818?mt=12

# Directory Contents
25ja002_fig1_data
`-- TokaGym
    |-- config
    |   |-- 140kA.yaml
    |   |-- 170kA.yaml
    |   `-- calc_targs.ipynb
    |-- data
    |   |-- 0025-misty-surf
    |   |   `-- topk_0004900.npz
    |   |-- 0057-glamo-sun
    |   |   `-- topk_0009000.npz
    |   |-- 0085-dazzl-water
    |   |   `-- topk_0017400.npz
    |   |-- 929020.npz
    |   |-- cached_high_level.nc
    |   |-- cached_low_current_high_level.nc
    |   |-- experiment_high_level.nc
    |   |-- fast_thom_demo.nc
    |   |-- final_fine_tuned_validation.nc
    |   |-- gap_robustness.nc
    |   |-- improve_140kA.nc
    |   |-- initial_training_validation.nc
    |   |-- intro_rd_shot.nc
    |   |-- ip_wtot_at_disrupt.nc
    |   |-- last_run_day_140kA_predictions.nc
    |   |-- last_run_day_170kA_predictions.nc
    |   |-- ntm.nc
    |   |-- prediction_plots.nc
    |   |-- prediction_plots_thomson.nc
    |   |-- profile_predictor_val_data.nc
    |   |-- rshift_debug.nc
    |   |-- thomson_bc_example.nc
    |   |-- TSno78157.h5
    |   |-- TSno82877.h5
    |   `-- TSno82878.h5
    |-- jaxrl
    |   |-- constr_ppo.py
    |   |-- constr_ppo_trainer.py
    |   |-- env.py
    |   |-- env_types.py
    |   |-- helpers.py
    |   |-- __init__.py
    |   |-- networks
    |   |   |-- __init__.py
    |   |   |-- mlp.py
    |   |   |-- network_utils.py
    |   |   |-- policy.py
    |   |   |-- pos_embed.py
    |   |   |-- pytree_input.py
    |   |   `-- value.py
    |   |-- ppo.py
    |   |-- ppo_trainer.py
    |   `-- utils
    |       |-- ckpt_manager.py
    |       |-- grad_utils.py
    |       |-- __init__.py
    |       |-- iter_utils.py
    |       |-- jax_types.py
    |       |-- jax_utils.py
    |       |-- logging.py
    |       |-- none.py
    |       |-- schedule.py
    |       |-- shape_utils.py
    |       |-- tfp.py
    |       `-- train_state.py
    |-- matplotlibrc
    |-- notebooks
    |   |-- check_data.ipynb
    |   |-- evaluate_model.ipynb
    |   |-- fetch_ip_wtot_disrupt.ipynb
    |   |-- find_good_baseline_shot.ipynb
    |   |-- limits_analysis.ipynb
    |   |-- paper_plot_generation
    |   |   |-- gap_robustness.ipynb
    |   |   |-- high_level_results.ipynb
    |   |   |-- improve_140.ipynb
    |   |   |-- introductory_figure.ipynb
    |   |   |-- misc_plots.ipynb
    |   |   |-- model_val_plots.ipynb
    |   |   |-- ntm_check.ipynb
    |   |   |-- pca_commentary.ipynb
    |   |   |-- prediction_plots.ipynb
    |   |   `-- rshift_plot.ipynb
    |   |-- reward_model.ipynb
    |   |-- shape.ipynb
    |   |-- val_model.ipynb
    |   |-- vgr_counterfactual.ipynb
    |   `-- visualize_rollout.ipynb
    |-- oswin_contrax.patch
    |-- poetry.lock
    |-- pyproject.toml
    |-- README.md
    |-- scripts
    |   |-- eval_es_ff_traj.py
    |   |-- eval_ppo.py
    |   |-- plot_hand_ff_rollout.py
    |   |-- plot_time_embed2.py
    |   |-- plot_time_embed.py
    |   |-- pred_compare.ipynb
    |   |-- train_constr_ppo.py
    |   |-- train_es.py
    |   |-- train_ppo_fb.py
    |   |-- train_ppo.py
    |   |-- translate_points.ipynb
    |   `-- viz_rollouts.py
    |-- submodules
    |   `-- contrax
    |-- tests
    |   |-- __init__.py
    |   |-- test_env.py
    |   |-- test_gae_constr.py
    |   |-- test_gym.py
    |   |-- test_model_hook.py
    |   |-- test_samplers.py
    |   `-- test_types.py
    `-- toka_gym
        |-- constants.py
        |-- es_fitness_model.py
        |-- get_ppo.py
        |-- __init__.py
        |-- model_hook.py
        |-- path_utils.py
        |-- plotting.py
        |-- reward_model.py
        |-- samplers.py
        |-- shape.py
        |-- tcv_env.py
        |-- tcv_gym.py
        |-- types.py
        |-- utils.py
        |-- visualize.py
        |-- wandb_utils.py
        `-- xarray_utils.py
